ST-MOC

JCE-GW

ST-MOC is an advanced extension of the Multi-Order Coverage (MOC) data structure that integrates both spatial and temporal information, making it a powerful tool for planning observations in multi-messenger astronomy.

Based on HEALPix tessellation, this data structure enables the definition of when a sky region is observable within a given time interval from a specific observatory. It enriches electromagnetic (EM) follow-up strategies by simultaneously incorporating spatial and observability information.

 

Key Features:

  • VO Interoperability: ST-MOCs are a recommended standard by the IVOA (International Virtual Observatory Alliance) and are interoperable with Virtual Observatory (VO) tools and services.
  • Efficient operations: Thanks to its hierarchical design, operations between different skymaps—such as union, intersection —can be performed efficiently, enabling rapid analysis in time-critical applications.

Applications in Multi‑Messenger Observations

  • Gravitational‑Wave Follow‑Up: For transient events like kilonovae, ST‑MOC helps astronomers identify not only the sky regions with high GW localization probability but also when these regions will be visible from various observatories.
  • Coordinated Observing: ST‑MOC supports multi‑messenger campaigns by overlaying sky regions and observability windows from different facilities, enabling synchronized observations in optical, radio, neutrino, or X-ray bands.
  • Data Model and time window: ST-MOCs make it straightforward to adjust the time window when searching for coincident astrophysical events, allowing alignment with the temporal windows predicted by different theoretical models.
    • Functionality Overview:
      • Would you be interested in exploring a technical notebook example, reviewing an API reference, or seeing integration tips with event brokers or telescope scheduling systems?
      • Are you interested in adding a time window to a gravitational-wave skymap and identifying simultaneous space-time intersections with high-energy or neutrino events?
  • How can we apply spatial and temporal filters to a list of candidate transients?

  • Repositories & Tools: ST-MOCs are officially supported and developed within the Python library mocpy, which enables standardized usage across applications. The library allows easy creation and manipulation of MOCs (Multi-Order Coverage maps) and their extensions, such as ST-MOCs, with long-term support for development and maintenance.

We emphasize that ST-MOC is a recommended standard by the IVOA and is widely adopted across various tools and applications. Understanding the core library and supported APIs can be highly beneficial for integration, customization, and extending functionality. ST-MOC is not a standalone tool, but a data structure designed for integration into larger software frameworks, accompanied by dedicated, open-access documentation.

Link: mocpy